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R Examples

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R-Study
===

## Overview
R Examples

#### Programming with R

| directory | description | packages |
|-----------|-------------|---------|
| functional-programming         | functional programming in R            | {base}        |
| inside-r           | understand the internal implementation in R         | {pryr}        |
| meta-programming           | meta programming in R            | {base}        |

#### Data Preprocessing and Visualization

| directory | description | packages |
|-----------|-------------|---------|
| correlation | correlation | {psych}, {polycor}, {Kendall}, {vcdExtra}, {lsr} |
| data-generation | data generation | {MASS}  |
| data-handling         | data handling            | {dplyr}, {tidyr}, {purrr}, {dummies}        |
| ggplot2          | visualization            | {ggplot2}, {GGally}, {ggfortify}        |
| reading-data          | reading data            | {data.table}, {jsonlite}, {jqr}, {readxl}, {openxlsx}, {RMySQL}, {aws.s3}       |
| stats          | basic statistics            | {base}        |
| strings          | string manipulation in R            | {stringr}        |
| transformation          | Box-Cox transformation            | {car}        |
| lubridate          | Make Dealing with Dates            | {lubridate}        |

#### Statistical Model

| directory | description | packages |
|-----------|-------------|---------|
| discrete-choice-model          | discrete choice model            | {mlogit}, {MASS}, {ordinal}        |
| glm          | generalized linear model            | {stats}, {ROCR}        |
| lda          | linear discriminant            | {MASS}        |
| lm          | linear model            | {stats}        |
| lme          | linear mixed effects model            | {lme4}        |
| pca          | principal component analysis            | {kernlab}        |
| regularization          | L1/L2 regularization and elastic net            | {glmnet}, {useful}        |
| stan          | MCMC (NUTS)            | {rstan}        |
| testing          | statistical hypothesis testing            | {lawstat}, {pwr}        |

#### Statistical Machine Learning

| directory | description | packages |
|-----------|-------------|---------|
| bayesian-network        |  bayesian-network           | {bnlearn}        |
| cca          | canonical correlation analysis            | {kernlab}        |
| gradient-boosting          | gradient boosting            | {xgboost}        |
| knn          | k-nearest neighbor            | {class}, {FNN}        |
| kmeans          | k-means clustering            | {stats}        |
| random-forest          | Random Forest            | {randomForest}        |
| recommender          | recommendation algorithms            | {recommenderlab}        |
| naive-bayes          | naive bayes            | {e1071}        |
| svm          | support vector machine            | {kernlab}, {caret}        |

#### Time Series Analysis

| directory | description | packages |
|-----------|-------------|---------|
| arima |   AR, ARMA, ARIMA models          | {stats}        |
| dlm         | dynamic Linear models            | {dlm}        |
| forecast          | econometric method            | {tseries}, {forecast}, {quantmod}, {PerformanceAnalytics}        |
| garch          | GARCH and VaR models           | {rugarch}        |
| var         | VAR model            | {vars}        |

#### Others

| directory | description | packages |
|-----------|-------------|---------|
| arules        |  association rules           |   {arules}      |
| causality         |  Causality Analysis           | {Matching}, {fastICA}         |
| design-of-experiments          | design of experiments            | {DoE.base}        |

## Licence
[MIT](http://opensource.org/licenses/MIT)

## Author
[t2sy](https://github.com/fisproject)

R-Study

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